Alternative Splicing, Internal Promoter, Nonsense-Mediated Decay, or All Three: Explaining the Distribution of Truncation Variants in Titin. (October 2016)

• Record Type: Journal Article
• Authors: Deo, Rahul C.
• Is Part Of: Circulation. Volume 9:Number 5(2016)
• Publication Date: 2016-10
• Subjects: alternative splicing -- confusion -- dilated cardiomyopathy -- human -- mutation; Arrhythmia -- Periodicals; Heart -- Electric properties -- Periodicals; 616.1042
• DOI: 10.1161/CIRCGENETICS.116.001513
• Languages: English
• ISSNs: 1942-325X

Abstract

Abstract : Background—: Truncating mutations in the giant sarcomeric gene Titin are the most common type of genetic alteration in dilated cardiomyopathy. Detailed studies have amassed a wealth of information about truncating variant position in cases and controls. Nonetheless, considerable confusion exists as to how to interpret the pathogenicity of these variants, hindering our ability to make useful recommendations to patients. Methods and Results—: Building on our recent discovery of a conserved internal promoter within the Titin gene, we sought to develop an integrative statistical model to explain the observed pattern of Titin truncation variants in patients with dilated cardiomyopathy and population controls. We amassed Titin truncation mutation information from 1714 human dilated cardiomyopathy cases and >69 000 controls and found 3 factors explaining the distribution of Titin mutations: (1) alternative splicing, (2) whether the internal promoter Cronos isoform was disrupted, and (3) whether the distal C terminus was targeted (in keeping with the observation that truncation variants in this region escape nonsense-mediated decay and continue to be incorporated in the sarcomere). A model using these 3 factors had strong predictive performance with an area under the receiver operating characteristic curve of 0.81. Accordingly, individuals with either the most severe form of dilated cardiomyopathy or whose mutations demonstrated clear family segregation experienced the highest risk profile across all 3 components. Conclusions—: We conclude that quantitative models derived from large-scale human genetic and phenotypic data can be applied to help overcome the ever-growing challenges of genetic data interpretation. Results of our approach can be found athttp://cvri.ucsf.edu/~deo/TTNtruncationvariant.html . Abstract : Supplemental Digital Content is available in the text.